[yt-svn] commit/yt: jzuhone: Merged in MatthewTurk/yt/yt-3.0 (pull request #974)

commits-noreply at bitbucket.org commits-noreply at bitbucket.org
Mon Jul 14 10:45:54 PDT 2014


1 new commit in yt:

https://bitbucket.org/yt_analysis/yt/commits/09146962c600/
Changeset:   09146962c600
Branch:      yt-3.0
User:        jzuhone
Date:        2014-07-14 19:45:42
Summary:     Merged in MatthewTurk/yt/yt-3.0 (pull request #974)

Fixing non-Cartesian flash bounding box
Affected #:  1 file

diff -r d091dd64ed463b8feae5398375e8ab327baeb47a -r 09146962c600a00acc3200043f73f44bd0221f3b yt/frontends/flash/data_structures.py
--- a/yt/frontends/flash/data_structures.py
+++ b/yt/frontends/flash/data_structures.py
@@ -141,11 +141,21 @@
         # Because we don't care about units, we're going to operate on views.
         gle = self.grid_left_edge.ndarray_view()
         gre = self.grid_right_edge.ndarray_view()
+        geom = self.parameter_file.geometry
+        if geom != 'cartesian' and ND < 3:
+            if geom == 'spherical' and ND < 2:
+                gle[:,1] = 0.0
+                gre[:,1] = np.pi
+            gle[:,2] = 0.0
+            gre[:,2] = 2.0 * np.pi
+            return
+
+        # Now, for cartesian data.
         for i in xrange(self.num_grids):
             dx = dxs[self.grid_levels[i],:]
             gle[i][:ND] = np.rint(gle[i][:ND]/dx[0][:ND])*dx[0][:ND]
             gre[i][:ND] = np.rint(gre[i][:ND]/dx[0][:ND])*dx[0][:ND]
-                        
+
     def _populate_grid_objects(self):
         # We only handle 3D data, so offset is 7 (nfaces+1)
         
@@ -363,6 +373,9 @@
         elif self.dimensionality < 3 and self.geometry == "polar":
             mylog.warning("Extending theta dimension to 2PI + left edge.")
             self.domain_right_edge[1] = self.domain_left_edge[1] + 2*np.pi
+        elif self.dimensionality < 3 and self.geometry == "spherical":
+            mylog.warning("Extending phi dimension to 2PI + left edge.")
+            self.domain_right_edge[2] = self.domain_left_edge[2] + 2*np.pi
         self.domain_dimensions = \
             np.array([nblockx*nxb,nblocky*nyb,nblockz*nzb])

Repository URL: https://bitbucket.org/yt_analysis/yt/

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